2/ To start, look for the #canonical tag in the flags column of the transcript table. The canonical transcript is based on conservation, expression, concordance with @appris_cnio and @uniprot, length, clinically important variants and completeness.
3/ Many Ensembl #canonical transcripts will also be the #MANESelect, which is our collaboration with @NCBI. These transcripts match perfectly with RefSeq transcripts, so are the best to report variant location.
4/ Some genes have mutually exclusive exons which are clinically important. These genes may also have a #MANEPlusClinical, a second transcript with the other exon, and you should report variant positions in both.
5/ ⚠️WARNING ⚠️ The MANE project has only focussed on human protein coding genes on the human GRCh38 assembly, so MANE Select or MANE Plus Clinical transcripts are only annotated for this assembly.
6/ ⚠️WARNING ⚠️: Don’t use the transcript numbers (eg LAMA3-201) or transcripts IDs (eg ENST00000269217) as rankings or a guide for choosing. Both are completely arbitrary and only the ENSTs are stable between releases.
7/ Whatever you use to report, note down the transcript stable ID with the version number, eg ENST00000313654.14. Transcripts change and can differ between databases. Only way to be 100% clear about which sequence is with a versioned stable identifier.
2/ If you need the sequence of a single #gene, you can search for the gene symbol or ID from Ensembl homepage and click on ‘Sequence’ in the menu on the left
3/ From this page, you can download the sequence of the gene by clicking on the blue ‘Download Sequence’ button just above the sequence display.
1/ It’s another Thursday, and that means it’s time for another #tweetorial! Today, we want to show you how you can view RefSeq #annotations on Ensembl 🥳
2/ While Ensembl gene models are annotated directly on the reference genome, #RefSeq are annotated on mRNA sequences. In other words: genome browsers will have different annotation methods, so you might be interested in comparing these annotations side-by-side 📖🤔
3/ 👂🏽You say you want to make direct comparisons of annotations between @NCBI’s RefSeq and Ensembl? Now is your time to try it out on Ensembl! 🏃🏽
2/ The Variant Effect Predictor (VEP) is what you’re going to need for this task. You can find it in the blue header from the @ensembl homepage: ensembl.org/info/docs/tool…
3/ Click the ‘Launch VEP’ button to open the VEP web tool and enter your input data using instructions in the documentation:
👉ensembl.org/info/docs/tool…
1/ Do you need reference sequence files from #Ensembl? All of the different files available can be confusing. Here’s a thread to help you decide which files you need…🧵
2/ The way you approach this problem will depend on if you are starting with a #gene of interest or if you already have the ID (e.g rs699) of a variant for which you want to find the observed allele frequencies.
3/ If you are starting with a gene, search for the gene name or ID from the #Ensembl homepage and navigate to the Gene tab.
Want to learn about a gene function, but there’s no functional data in your species of interest? Or maybe looking for a homologue of your fav gene in a model organism to carry out functional work? Look no further! This #tweetorial will show you how to find orthologues in @ensembl
2/14
Let’s start on the Ensembl homepage and search for our #gene of interest SCP2 by typing its name into the search box. Then go to the gene tab by clicking on the gene name in the search results.
3/14
You can learn more about the #gene function by exploring gene ontology terms and associated phenotypes. Let’s click on Phenotypes in the side menu. This view shows phenotypes associated with our gene of interest and variants in this gene.